Displaying 1 to 19 from 19 results

Machine-Learning-Tutorials - machine learning and deep learning tutorials, articles and other resources

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This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resources. Other awesome lists can be found in this list. If you want to contribute to this list, please read Contributing Guidelines.

awesome-datascience - :memo: An awesome Data Science repository to learn and apply for real world problems

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An open source Data Science repository to learn and apply towards solving real world problems. First of all, Data Science is one of the hottest topics on the Computer and Internet farmland nowadays. People have gathered data from applications and systems until today and now is the time to analyze them. The next steps are producing suggestions from the data and creating predictions about the future. Here you can find the biggest question for Data Science and hundreds of answers from experts. Our favorite data scientist is Clare Corthell. She is an expert in data-related systems and a hacker, and has been working on a company as a data scientist. Clare's blog. This website helps you to understand the exact way to study as a professional data scientist.




deep-learning-model-convertor - The convertor/conversion of deep learning models for different deep learning frameworks/softwares

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Note: This is not one convertor for all frameworks, but a collection of different converters. Because github is an open source platform, I hope we can help each other here, gather everyone's strength. The sheet below is a overview of all convertors in github (not only contain official provided and more are user-self implementations). I just make a little work to collect these convertors. Also, hope everyone can support this project to help more people who're also crazy because of various frameworks.

Awesome-Deep-Learning-Resources - Rough list of my favorite deep learning resources, useful for revisiting topics or for reference

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This is a rough list of my favorite deep learning resources. It has been useful to me for learning how to do deep learning, I use it for revisiting topics or for reference. I (Guillaume Chevalier) have built this list and got through all of the content listed here, carefully. You might also want to look at Andrej Karpathy's new post about trends in Machine Learning research.


awesome-deep-learning-music - List of articles related to deep learning applied to music

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By Yann Bayle (Website, GitHub) from LaBRI (Website, Twitter), Univ. Bordeaux (Website, Twitter), CNRS (Website, Twitter) and SCRIME (Website). The role of this curated list is to gather scientific articles, thesis and reports that use deep learning approaches applied to music. The list is currently under construction but feel free to contribute to the missing fields and to add other resources! To do so, please refer to the How To Contribute section. The resources provided here come from my review of the state-of-the-art for my PhD Thesis for which an article is being written. There are already surveys on deep learning for music generation, speech separation and speaker identification. However, these surveys do not cover music information retrieval tasks that are included in this repository.

Deep-Learning-for-Medical-Applications - Deep Learning Papers on Medical Image Analysis

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To the best of our knowledge, this is the first list of deep learning papers on medical applications. There are couple of lists for deep learning papers in general, or computer vision, for example Awesome Deep Learning Papers. In this list, I try to classify the papers based on their deep learning techniques and learning methodology. I believe this list could be a good starting point for DL researchers on Medical Applications.

CatPapers - Cool vision, learning, and graphics papers on Cats!

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As reported by Cisco, 90% of net traffic will be visual, and indeed, most of the visual data are cat photos and videos. Thus, understanding, modeling and synthesizing our feline friends becomes a more and more important research problem these days, especially for our cat lovers. Cat Paper Collection is an academic paper collection that includes computer graphics, computer vision, machine learning and human-computer interaction papers that produce experimental results related to cats. If you want to add/remove a paper, please send an email to Jun-Yan Zhu (junyanz at berkeley dot edu).

awesome-sentiment-analysis - 😀😄😂😭 A curated list of Sentiment Analysis methods, implementations and misc

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Curated list of Sentiment Analysis methods, implementations and misc. The goal of this repository is to provide adequate links for scholars who want to research in this domain; and at the same time, be sufficiently accessible for developers who want to integrate sentiment analysis into their applications.

awesome-very-deep-learning - 🔥A curated list of papers and code about very deep neural networks

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awesome-very-deep-learning is a curated list for papers and code about implementing and training very deep neural networks. Value Iteration Networks are very deep networks that have tied weights and perform approximate value iteration. They are used as an internal (model-based) planning module.

awesome-capsule-networks - A curated list of awesome resources related to capsule networks

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A curated list of awesome resources related to capsule networks maintained by AI Summary. Please pull a request if you are aware of additional resources.

awesome-h2o - A curated list of research, applications and projects built using H2O Machine Learning

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Below is a curated list of all the awesome projects, applications, research, tutorials, courses and books that use H2O, an open source, distributed machine learning platform. H2O offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models, Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox Proportional Hazards, K-means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (AutoML). H2O.ai produces many tutorials, blog posts, presentations and videos about H2O, but the list below is comprised of awesome content produced by the greater H2O user community.

awesome-embedded-ai - Curated list of awesome AI resources about embedded and mobile devices

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This awesome list will be continually updated. Besides, you can read new bi-weekly-reports: PerfXLab/embedded_ai. A curated list of awesome A.I. & Embedded/Mobile-devices resources, tools and more.

my-awesome-AI-bookmarks - Curated list of my reads, implementations and core concepts of Artificial Intelligence, Deep Learning, Machine Learning by best folk in the world

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Curated list of my reads, implementations and core concepts of Artificial Intelligence, Deep Learning, Machine Learning by best folk in the world. Have anything in mind that you think is awesome and would fit in this list? Feel free to send a pull request.

awesomeMLmath - Curated list to learn the math basics for machine learning

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Curated list to learn the math basics for machine learning. Note that this is a biased list from a Deep Learning researcher. The main topics are Calculus, Linear Algebra, Statistics, Probability and Signal Processing. If you "combine" Probability with Signal Processing you have Stochastic Processes which is the theory behind RNN, Kalman Filters, etc.